Characterizing walleye pollock (Theragra chalcogramma) winter distribution from opportunistic acoustic data

In 2003, acoustic data from 25 000 km of ship track lines were collected from two fishing vessels participating in the eastern Bering Sea walleye pollock (Theragra chalcogramma) fishery. Although these data were not calibrated or collected on a systematic grid, their broad temporal extent combined with high spatial resolution facilitated the examination of the distribution and behaviour of fished aggregations. To demonstrate their scientific applicability, these data were used to identify the spatio-temporal dynamics of pollock aggregations over scales ranging from hundreds of metres to hundreds of kilometres and from minutes to months. The spatial analysis identified three levels of pollock aggregation. The largest regions of high pollock density had an average diameter of 110 km and were comparable with distinct fishing grounds identified by fishers. The next smaller areas of high pollock density had a diameter between 2.5 and 6 km. Within these areas were clusters of pollock at even higher densities. The extent of the smallest aggregations ranged in diameter from 0.1 km in daylight to 0.6 km at night. Time-series analysis identified vertical and horizontal diel changes in pollock distribution and an overall decline in pollock density over the study period.

[1]  E. K. Pikitch,et al.  Ecosystem-Based Fishery Management , 2004, Science.

[2]  Steven J. D. Martell,et al.  Fisheries Ecology and Management , 2004 .

[3]  Christophe Guinet,et al.  Foraging ground fidelity and route-choice tactics of a marine predator: the Antarctic fur seal Arctocephalus gazella , 2001 .

[4]  C. Walters,et al.  Quantitative fisheries stock assessment: Choice, dynamics and uncertainty , 2004, Reviews in Fish Biology and Fisheries.

[5]  Simon F. Thrush,et al.  DISTURBANCE OF THE MARINE BENTHIC HABITAT BY COMMERCIAL FISHING: IMPACTS AT THE SCALE OF THE FISHERY , 1998 .

[6]  M. Dorn.  Fishing behavior of factory trawlers: a hierarchical model of information processing and decision-making , 2001 .

[7]  A. Haynie,et al.  An expected profit model for monetizing fishing location choices , 2010 .

[8]  Troy W. Hartley,et al.  Emergence of multi-stakeholder-driven cooperative research in the Northwest Atlantic: The case of the Northeast Consortium , 2006, Marine Policy.

[9]  J. Kelley,et al.  Seasonal changes in the diel vertical migration of walleye pollock (Theragra chalcogramma) in the northern Gulf of Alaska , 2009, Environmental Biology of Fishes.

[10]  Christopher D. Wilson,et al.  Marine predators and persistent prey in the southeast Bering Sea , 2012 .

[11]  Gerjan J. Piet,et al.  The importance of scale for fishing impact estimations , 2009 .

[12]  B. L. Olla,et al.  Diel patterns of behavior in juvenile walleye pollock,Theragra chalcogramma , 1996, Environmental Biology of Fishes.

[13]  J. Piatt,et al.  Scale-dependent correlation of seabirds with schooling fish in a coastal ecosystem , 1986 .

[14]  Paul G. Fernandes,et al.  A consistent approach to definitions and symbols in fisheries acoustics , 2002 .

[15]  Kjell Einar Erikstad,et al.  SCALE‐DEPENDENT PREDATOR–PREY INTERACTIONS: THE HIERARCHICAL SPATIAL DISTRIBUTION OF SEABIRDS AND PREY , 2000 .

[16]  William A. Montevecchi,et al.  SEARCH STRATEGIES OF A PURSUIT-DIVING MARINE BIRD AND THE PERSISTENCE OF PREY PATCHES , 2003 .

[17]  Pierre Fréon,et al.  Dynamics of pelagic fish distribution and behaviour : effects on fisheries and stock assessment , 1999 .

[18]  J. Wilen,et al.  Dissecting the tragedy: A spatial model of behavior in the commons , 2011 .

[19]  C. Ryer,et al.  Effect of light on juvenile walleye pollock shoaling and their interaction with predators , 1998 .

[20]  D. L. Alverson,et al.  A study of demersal fishes and fisheries of the Northeastern Pacific Ocean , 1964 .

[21]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[22]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[23]  E. John Simmonds,et al.  Fisheries Acoustics: Theory and Practice , 2005 .

[24]  G. Macaulay,et al.  Using fish-processing time to carry out acoustic surveys from commercial vessels , 2005 .

[25]  P. Walline.  Geostatistical simulations of eastern Bering Sea walleye pollock spatial distributions, to estimate sampling precision , 2007 .

[26]  N. Cressie,et al.  Statistics for Spatial Data. , 1992 .

[27]  W. Falck,et al.  Nonparametric spatial covariance functions: Estimation and testing , 2001, Environmental and Ecological Statistics.

[28]  Spatial and temporal variance of walleye pollock (Theragra chalcogramma) in the eastern Bering Sea , 2005 .

[29]  H. Knudsen.  Long-term evaluation of scientific-echosounder performance , 2009 .

[30]  R. Haining.  Spatial Data Analysis in the Social and Environmental Sciences , 1990 .

[31]  C. Walters,et al.  Quantitative Fisheries Stock Assessment , 1992, Springer US.

[32]  W. A. Karp.  Collection of acoustic data from fishing vessels , 2007 .

[33]  N. Williamson,et al.  Results of the Echo Integration-Trawl Survey of Walleye Pollock (Theragra chalcogramma) on the U.S. and Russian , 2008 .

[34]  E. Shaw.  The Development of Schooling in Fishes. II , 1961, Physiological Zoology.

[35]  J. Horne,et al.  Characterization and classification of acoustically detected fish spatial distributions , 2008 .

[36]  P. Brehmer,et al.  Fisheries Acoustics: Theory and Practice, 2nd edn , 2006 .

[37]  K. Bailey,et al.  Population Structure and Dynamics of Walleye Pollock, Theragra chalcogramma , 1999 .

[38]  William N. Venables,et al.  Modern Applied Statistics with S , 2010 .